GPT-5.2 Pro vs GLM 5
GPT-5.2 Pro (OpenAI, released 2025-12-10) and GLM 5 (Z.ai, released 2026-02-11) sit at opposite ends of the price-performance curve. GPT-5.2 Pro is a closed, multimodal, reasoning-mandatory model built for complex agentic and long-context tasks. GLM 5 is an open-source, text-only model tuned for large-scale programming and long-horizon agent work, with published Design Arena rankings across 12 categories. The gap that matters most: input tokens on GPT-5.2 Pro cost 35x what they cost on GLM 5.
Spec vs spec
| Spec | GPT-5.2 Pro | GLM 5 |
|---|---|---|
| Context window | 400K | 203K |
| Max output | 128K | — |
| Input modalities | image, text, file | text |
| Output modalities | text | text |
| Released | Dec 10, 2025 | Feb 11, 2026 |
| Reasoning | always on | optional |
Pricing
Per 1M tokens. Provider price plus the flat 3% fee — the sum is what you pay.
openai/gpt-5.2-pro
Input · 1M tokens
$21.00 + 3%$21.63
Output · 1M tokens
$168.00 + 3%$173.04
FEE — FLAT, EVERY MODEL3%
z-ai/glm-5
Input · 1M tokens
$0.600 + 3%$0.618
Output · 1M tokens
$1.92 + 3%$1.98
Cache read · 1M tokens
$0.120 + 3%$0.124
FEE — FLAT, EVERY MODEL3%
One workload, priced on both
10M input + 2M output tokens at each model's price, flat 3% fee included.
openai/gpt-5.2-pro
$562.38
$546.00 provider + 3%
z-ai/glm-5Cheaper
$10.14
$9.84 provider + 3%
Pricing math
On OpenKey, provider price gets a flat 3% fee added: GPT-5.2 Pro runs $21.00 prompt / $168.00 completion per 1M tokens from OpenAI, so OpenKey lists it at $21.63 / $173.04 (21.00 × 1.03, 168.00 × 1.03). GLM 5 runs $0.60 prompt / $1.92 completion, becoming $0.618 / $1.9776 on OpenKey. For a 10M-input/2M-output workload, GPT-5.2 Pro totals $546.00 and GLM 5 totals $9.84 — the computed input price ratio is 35x. GLM 5 also has a cache-read rate of $0.12/1M tokens on the provider side, which GPT-5.2 Pro's record doesn't list, giving GLM 5 another lever for repeat-context workloads.
Coding and agent performance
GLM 5 has published Design Arena results: rank 3 in godotgamedev (elo 1237, 54.8% win rate), rank 6 in androidnative agents (elo 1244, 62% win rate), rank 10 in mobileapps agents (elo 1222, 53.1% win rate), and rank 13 in fullstack agents (elo 1190, 52.8% win rate). Across the models arena it lands rank 15 on gamedev and 3d, rank 16 on codecategories, and rank 18-22 on website, uicomponent, svg, and dataviz. GPT-5.2 Pro has no benchmark data in this record, so any coding-quality comparison has to rely on GLM 5's numbers alone plus GPT-5.2 Pro's stated design intent (agentic coding and long-context improvements over GPT-5 Pro).
Context and modality
GPT-5.2 Pro supports a 400,000-token context window against GLM 5's 202,752 tokens — a context ratio of 1.97x in GPT-5.2 Pro's favor. GPT-5.2 Pro also accepts image, text, and file input (output text-only), while GLM 5 is text-to-text only. GPT-5.2 Pro caps completions at 128,000 tokens; GLM 5's max completion isn't specified in its record. If your job involves parsing documents or images alongside code, GPT-5.2 Pro is the only option of the two; if it's pure text at scale, the extra context headroom on GPT-5.2 Pro rarely offsets its cost.
Reasoning behavior
GPT-5.2 Pro makes reasoning mandatory, with effort levels of xhigh, high, and medium (default medium) — you can't turn it off, which affects both latency and cost per call. GLM 5 makes reasoning optional but enabled by default, giving you a lever to disable it for simpler calls. GLM 5 also exposes a wider parameter surface (frequency_penalty, logit_bias, logprobs, min_p, top_k, top_logprobs, and more) versus GPT-5.2 Pro's narrower set (reasoning, response_format, seed, structured_outputs, tool_choice, tools). If you need fine-grained sampling control, GLM 5's parameter list gives you more to work with.
Which model for which job
| Use case | Pick | Why |
|---|---|---|
| High-volume code generation | GLM 5 | $9.84 vs $546.00 for the same 10M-in/2M-out workload |
| Document or image analysis | GPT-5.2 Pro | Only model of the two with image and file input support |
| Long-document reasoning | GPT-5.2 Pro | 400,000-token context vs GLM 5's 202,752, a 1.97x edge |
| Android-native agent tasks | GLM 5 | Rank 6 with a 62% win rate in Design Arena's androidnative category |
| Cost-capped experimentation | GLM 5 | Input tokens priced at $0.618/1M on OpenKey vs $21.63/1M for GPT-5.2 Pro |
| Tasks needing full sampling control | GLM 5 | Supports top_k, top_logprobs, min_p, and logit_bias; GPT-5.2 Pro doesn't |
Questions
- How much cheaper is GLM 5 than GPT-5.2 Pro?
- For a 10M-input/2M-output workload, GLM 5 costs $9.84 on OpenKey versus $546.00 for GPT-5.2 Pro. The input price ratio alone is 35x — GPT-5.2 Pro's OpenKey input price is $21.63/1M tokens against GLM 5's $0.618/1M.
- Which model has the bigger context window?
- GPT-5.2 Pro supports 400,000 tokens of context versus GLM 5's 202,752 tokens, a ratio of 1.97x. If you're processing very long documents or codebases in a single call, that gap can matter more than the price difference.
- Can GLM 5 handle images or files?
- No. GLM 5 is text-to-text only. GPT-5.2 Pro accepts image, text, and file input (output remains text), so any workload involving screenshots, PDFs, or scanned documents needs GPT-5.2 Pro.
- Is reasoning always on for GPT-5.2 Pro?
- Yes, reasoning is mandatory on GPT-5.2 Pro with effort levels xhigh, high, or medium (default medium). GLM 5 has reasoning enabled by default but it's optional, so you can disable it for simpler, cheaper calls.